{"id":"https://openalex.org/W1871569676","doi":"https://doi.org/10.1109/icassp.1985.1168172","title":"Contour vector quantization and waveform coding","display_name":"Contour vector quantization and waveform coding","publication_year":2005,"publication_date":"2005-03-23","ids":{"openalex":"https://openalex.org/W1871569676","doi":"https://doi.org/10.1109/icassp.1985.1168172","mag":"1871569676"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1985.1168172","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168172","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044941545","display_name":"T.R. Fischer","orcid":"https://orcid.org/0000-0002-2987-0478"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"T. Fischer","raw_affiliation_strings":["Department of Electrical Engineering, Texas A and M University, USA","Texas A&M Univ., College station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Texas A and M University, USA","institution_ids":["https://openalex.org/I91045830"]},{"raw_affiliation_string":"Texas A&M Univ., College station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054194121","display_name":"Kevin T. Malone","orcid":null},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K. Malone","raw_affiliation_strings":["Department of Electrical Engineering, Texas A and M University, USA","Department of Electrical Engineering, Texas A & M University, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Texas A and M University, USA","institution_ids":["https://openalex.org/I91045830"]},{"raw_affiliation_string":"Department of Electrical Engineering, Texas A & M University, USA","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5044941545"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.08764231,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"1707","last_page":"1710"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11034","display_name":"Digital Filter Design and Implementation","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.7992262840270996},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5595060586929321},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.538038969039917},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5123430490493774},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5114372968673706},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4872516691684723},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.47488826513290405},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.4679962992668152},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45914411544799805},{"id":"https://openalex.org/keywords/ergodic-theory","display_name":"Ergodic theory","score":0.45701438188552856},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.43557676672935486},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4213864803314209},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.41424381732940674},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.320629745721817},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1458931863307953},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.13443300127983093},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08255505561828613}],"concepts":[{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.7992262840270996},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5595060586929321},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.538038969039917},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5123430490493774},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5114372968673706},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4872516691684723},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.47488826513290405},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.4679962992668152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45914411544799805},{"id":"https://openalex.org/C122044880","wikidata":"https://www.wikidata.org/wiki/Q5498822","display_name":"Ergodic theory","level":2,"score":0.45701438188552856},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.43557676672935486},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4213864803314209},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.41424381732940674},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.320629745721817},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1458931863307953},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.13443300127983093},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08255505561828613},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1985.1168172","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168172","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1950316085","https://openalex.org/W1968127489","https://openalex.org/W1969012167","https://openalex.org/W1973387369","https://openalex.org/W1984034733","https://openalex.org/W1995875735","https://openalex.org/W2029495080","https://openalex.org/W2036845965","https://openalex.org/W2040336387","https://openalex.org/W2044002522","https://openalex.org/W2054128110","https://openalex.org/W2058075673","https://openalex.org/W2089419199","https://openalex.org/W2114283721","https://openalex.org/W2119352491","https://openalex.org/W2120788459","https://openalex.org/W2134383396","https://openalex.org/W2138054245","https://openalex.org/W2142228262","https://openalex.org/W2144452965","https://openalex.org/W2150593711","https://openalex.org/W2913399920","https://openalex.org/W2998892371","https://openalex.org/W4244017338","https://openalex.org/W4401325430","https://openalex.org/W6772764035"],"related_works":["https://openalex.org/W50969306","https://openalex.org/W2390585021","https://openalex.org/W412641959","https://openalex.org/W2341040961","https://openalex.org/W2779828239","https://openalex.org/W3154976382","https://openalex.org/W4292101436","https://openalex.org/W2044004505","https://openalex.org/W4287207389","https://openalex.org/W2951177262"],"abstract_inverted_index":{"Motivated":[0],"by":[1],"the":[2,32,36,43,49,70,92],"implicit":[3],"geometry":[4],"of":[5,22,35,42,51,72],"a":[6,10,20,73],"stationary,":[7],"ergodic":[8],"process,":[9],"vector":[11],"quantizer":[12],"(VQ)":[13],"design":[14,71],"algorithm":[15],"is":[16,28,59,84],"proposed,":[17],"based":[18,89],"on":[19],"contour":[21,74],"constant":[23],"probability":[24],"density.":[25],"The":[26,79],"approach":[27],"explicitly":[29],"related":[30],"to":[31,45],"differential":[33],"entropy":[34],"source,":[37],"and":[38,63],"uses":[39],"this":[40],"characteristic":[41],"source":[44,58],"provide":[46],"structure":[47],"for":[48,69,77],"location":[50],"VQ":[52,76,88],"output,":[53],"vectors.":[54],"A":[55],"correlated":[56],"Gaussian":[57],"treated":[60],"in":[61,91],"detail":[62],"used":[64],"as":[65],"an":[66],"appropriate":[67],"model":[68],"gain":[75],"speech.":[78],"resulting":[80],"mean-square":[81],"error":[82],"performance":[83],"competitive":[85],"with":[86],"alternative":[87],"results":[90],"literature.":[93]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
